

I don’t know: it’s not just the outputs posing a risk, but also the tools themselves
Yeah, that’s true. Poisoning the training corpus of models is at least a potential risk. There’s a whole field of AI security stuff out there now aimed at LLM security.
it shouldn’t require additional tools, checking for such common flaws.
Well, we are using them today for human programmers, so… :-)
























The point I’m making is that bash is optimized for quickly writing throwaway code. It doesn’t matter if the code written blows up in some case other than the one you’re using. You don’t need to handle edge cases that don’t apply to the one time that you will run the code. I write lots of bash code that doesn’t handle a bunch of edge cases, because for my one-off use, that edge case doesn’t arise. Similarly, if an LLMs is generating code that misses some edge case, if it’s a situation that will never arise, and that may not be a problem.
EDIT: I think maybe that you’re misunderstanding me as saying “all bash code is throwaway”, which isn’t true. I’m just using it as an example where throwaway code is a very common, substantial use case.